Statistical analysis of free-surface variability's impact on seismic wavefield

Abstract Time-lapse seismic monitoring is one of the critical technologies providing the active exploration of hydrocarbon deposits. In desert environments, many challenges are complicating its practical application. The paper deals with one of them – changes of topography due to a mobility of the sands. To assess this impact on the predictability, which is the measure of repeatability computed as cross-correlation of traces, the full numerical simulation is done. The primary attention is paid to the early arrivals because they are most sensitive to the change of a near-surface structure. This perturbation leads to the so-called “non-repeatable” noise which is one of the main trouble in time-lapse seismic monitoring. A standard measure to characterize a non-repeatable noise is to consider the energy of the difference if two data sets/images and compare it with the energy of each data/image. This value is known as the NRMS. If there is a perfect repeatability NRMS = 0, for random uncorrelated noise NRMS = 141%, and if the data sets are identical but polarity-reversed NRMS = 200%. In the paper, we demonstrate that for a homogeneous subsurface layer repeatability depends mainly on changes of the surface topography but not of its slope. At the same time, if one deals with a heterogeneous near-surface, repeatability is far worse for the zones with a thin sand layer (less than 5 m). There can happen significant non-repeatability with NRMS error greater than 60% and reduction of predictability below 75%. These values are similar to the NRMS measured on field data in Saudi Arabia, suggesting that such factors may be significant for land 4D seismic in a desert. Also, sand topography variations can be accumulated thus explaining experimentally observed trends showing that land seismic repeatability degrades over time from days to months and years.